In distributed data management systems, where data are stored on multiple computer nodes, various computer users and programs often require concurrent access to same data. When a transaction is to be performed on the data stored at one node, the effect that the transaction has on the data often needs to be reflected by the data stored at other nodes in the distributed system.
Existing distributed systems typically use transaction processing for maintaining a database in a known, consistent state, by ensuring that any operations carried out on the database that are interdependent are either all completed successfully or all cancelled successfully. If all operations of a transaction are completed successfully, the transaction is “committed” by the distributed system, and all changes to the database are made permanent. This is typically done using a commit operation. If any part of the transaction fails before it is committed, the database is restored back to the state it was in before the transaction began. This is done using a rollback operation.
One approach for providing rollback support requires logging all changes to data and undoing each change when a rollback is required. However, this approach has limited applicability, as only modifications that are reversible are supported. This approach also requires an elaborate logging mechanism.